The present description relates generally to methods of and apparatuses for evaluating the performance of a control system. More specifically, the present description relates to automated methods of and apparatuses for detecting and diagnosing oscillations in a feedback control loop.
Oscillating feedback control loops are a common occurrence in many types of control systems, such as heating, ventilating, and air conditioning (HVAC) systems. Oscillations are periodic changes that cause a signal within a feedback control loop to vary undesirably in a deterministic and repeatable fashion. Oscillating loops are undesirable because they increase variability in the quality of control and product performance, accelerate equipment wear, and may cause further oscillations in other interacting loops. Thus, detection, diagnosis, and correction of oscillations are important activities in feedback control loop supervision and maintenance.
Common causes of oscillations in feedback control loops include external oscillating disturbances, bad controller tuning, nonlinearities in a system component, such as static and dynamic nonlinearities, stiction (i.e., a sticking valve), incorrect component sizing, and poor actuator resolution, or a combination of these causes. Causes such as static and dynamic nonlinearities, stiction, incorrect component sizing, and poor actuator resolution are classified as system problems. External oscillating disturbances and bad controller tuning are classified as control problems.
Oscillation diagnosis involves distinguishing between these different causes of oscillations once they have been detected. Distinguishing between these types of causes is important for identifying appropriate remedial action. For example, attempts at re-tuning a controller will be unsuccessful or inefficient where a system problem is the cause of the oscillations rather than a control problem.
One problem with existing methods of detecting oscillations is that they require prior specification of an expected time parameter for the feedback control loop. Usually the information is required to configure a noise filter, or to set detection thresholds. This information is often unavailable or cannot be reliably estimated. Further, existing methods of diagnosing oscillations typically require a manual visual inspection of the shape of several different signals in the oscillating feedback control loop in order to distinguish between control problems and system problems. These requirements increase the required effort and costs associated with implementing the diagnosis method.
Thus, there is need for a method of and apparatus for evaluating the performance of a control system which does not require prior information about the feedback control loop being monitored. There is also need for an automated method of and apparatus for evaluating the performance of a control system that does not require manually monitoring shapes of multiple signals in the feedback control loop. There is further need for a method of and apparatus for evaluating the performance of a control system that is automated such that it does not require a manual visual inspection of a signal to distinguish among different causes of oscillations. There is yet further need for a method of and apparatus for evaluating the performance of a control system that is intuitive, easily implemented either directly or remotely, and requires minimal computational effort. There is yet further need for a method of and apparatus for evaluating the performance of a control system that is configured to address the effects of noise on the diagnosis while minimizing corruption to the monitored signal. There is yet further need for a method of and apparatus for evaluating the performance of a control system that is configured to address uncertainty in the diagnosis so that different feedback control loops may be compared.